Review of Ship Detection from Airborne Platforms

Fingas, Merv; Brown, Carl E.

doi:10.1080/07038992.2001.10854880

Cited by 34 publications

(15 citation statements)

References 15 publications

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“…Image defocusing or distortion problem results from the complex motions of ship has been a great challenge for the research in radar imaging, particularly the SAR imaging [1][2][3]. Moreover, the error caused by imaging distortion effects will become larger and larger with time accumulate.…”

Section: Introductionmentioning

confidence: 99%

3-D MIMO Radar Imaging of Ship Target with Rotational Motions

Wang¹,

Huang²,

Hu³

2019

RADIOENGINEERING

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The problem of image defocusing and distortion occurs in synthetic aperture radar (SAR) imaging of ship target with rotations. Although many literatures have analyzed this problem, it cannot efficiently be solved due to the coherent accumulation time for SAR target imaging, which results from their working principle and mechanism. In this paper, three-dimensional MIMO radar imaging of ship target with rotations is proposed. The real-time advantage of MIMO radar imaging is utilized to achieve high-precision imaging of ship target with rotations. Firstly, the ship rotations characteristics and imaging distortion effects are analyzed in detail. Then, the three-dimensional MIMO radar echo model is built to correct the scattering positions in time, geometrical analysis is carried out to analyze and optimize the target scattering coefficient variation process. Finally, a sparse imaging algorithm based on maximum a posterior (MAP) method is proposed to obtain accurate imaging result. Theoretical analysis and simulation results show that the three-dimensional imaging of ship target based on MIMO radar has better imaging accuracy and real-time performance compared with SAR, and can effectively solve the problem of image defocusing and distortion.

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Section: Introductionmentioning

confidence: 99%

3-D MIMO Radar Imaging of Ship Target with Rotational Motions

Wang¹,

Huang²,

Hu³

2019

RADIOENGINEERING

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“…Algorithms for ship detection include the amplitude based Constant False Alarm Rate (CFAR) which is the standard and most widely used algorithm [541][542][543], multi-look cross-correlation [515,525], along-track InSAR [521,527], polarimetric analysis (with and without CFAR) [516,518,523,524,526,528,529,531,532], and others (see review papers [533][534][535][536] for further information).…”

Section: Ship Detection and Identificationmentioning

confidence: 99%

“…Since then a substantial number of papers and review articles have been published, including those of , and also good review articles are available [533][534][535][536].…”

Section: Ship Detection and Identificationmentioning

confidence: 99%

Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics

2013

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The present article is an introductory paper in this special issue on synthetic aperture radar (SAR). A short review is presented on the recent trend and development of SAR and related techniques with selected topics, including the fields of applications, specifications of airborne and spaceborne SARs, and information contents in and interpretations of amplitude data, interferometric SAR (InSAR) data, and polarimetric SAR (PolSAR) data. The review is by no means extensive, and as such only brief summaries of of each selected topics and key references are provided. For further details, the readers are recommended to read the literature given in the references theirin.

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“…In the past few years, some traditional methods have been proposed for ship detection [1][2][3][4][5]. Some methods adopt the following ideas: Firstly, sea-land segmentation is carried out through the features of texture and shape, and the sea region is extracted as the region of interest (ROI).…”

Section: Introductionmentioning

confidence: 99%

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

et al. 2018

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Ship detection has been playing a significant role in the field of remote sensing for a long time, but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection, and the redundancy of the detection region. In order to solve these problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ships in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving problems resulting from the narrow width of the ship. Compared with previous multiscale detectors such as Feature Pyramid Network (FPN), DFPN builds high-level semantic feature-maps for all scales by means of dense connections, through which feature propagation is enhanced and feature reuse is encouraged. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multiscale region of interest (ROI) Align for the purpose of maintaining the completeness of the semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has state-of-the-art performance.

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Review of Ship Detection from Airborne Platforms

Cited by 34 publications

References 15 publications

3-D MIMO Radar Imaging of Ship Target with Rotational Motions

3-D MIMO Radar Imaging of Ship Target with Rotational Motions

Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

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